The present invention is related in general to memory controllers and more specifically to the design of a memory controller for use in an adaptive computing environment.
The advances made in the design and development of integrated circuits (“ICs”) have generally produced information-processing devices falling into one of several distinct types or categories having different properties and functions, such as microprocessors and digital signal processors (“DSPs”), application specific integrated circuits (“ASICs”), and field programmable gate arrays (“FPGAs”). Each of these different types or categories of information-processing devices have distinct advantages and disadvantages.
Microprocessors and DSPs, for example, typically provide a flexible, software-programmable solution for a wide variety of tasks. The flexibility of these devices requires a large amount of instruction decoding and processing, resulting in a comparatively small amount of processing resources devoted to actual algorithmic operations. Consequently, microprocessors and DSPs require significant processing resources, in the form of clock speed or silicon area, and consume significantly more power compared with other types of devices.
ASICs, while having comparative advantages in power consumption and size, use a fixed, “hard-wired” implementation of transistors to implement one or a small group of highly specific tasks. ASICs typically perform these tasks quite effectively; however, ASICs are not readily changeable, essentially requiring new masks and fabrication to realize any modifications to the intended tasks.
FPGAs allow a degree of post-fabrication modification, enabling some design and programming flexibility. FPGAs are comprised of small, repeating arrays of identical logic devices surrounded by several levels of programmable interconnects. Functions are implemented by configuring the interconnects to connect the logic devices in particular sequences and arrangements. Although FPGAs can be reconfigured after fabrication, the reconfiguring process is comparatively slow and is unsuitable for most real-time, immediate applications. Additionally, FPGAs are very expensive and very inefficient for implementation of particular functions. An algorithmic operation implemented on an FPGA may require orders of magnitude more silicon area, processing time, and power than its ASIC counterpart, particularly when the algorithm is a poor fit to the FPGA's array of homogeneous logic devices.
An adaptive computing engine (ACE) or adaptable computing machine (ACM) allows a collection of hardware resources to be rapidly configured for different tasks. Resources can include, e.g., processors, or nodes, for performing arithmetic, logical and other functions. The nodes are provided with an interconnection system that allows communication among nodes and communication with resources such as memory, input/output ports, etc.
One type of valuable processing includes input/output services to allow nodes to communicate with external components, devices or resources.